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# linear regression equation level of significance

Question 3

Are employees who work more hours per week less satisfied with their job? Data was collected from a random sample of 22 employees at a company on the following variables:

• Job satisfaction (measures 0 to 100)

• Total hours worked per week

 Coefficients Standard Error intercept 120.7223 16.8721 X variable 1 -1.2033 0.3188
1. which variable is the independent (explanatory) variable for this simple linear regression model? Which variable is the (response) dependent variable?

(b)State the simple linear regression equation

(c)Interpret the meaning of the slope coefficient estimate in this problem

(d)at the 0.05 level of significance, is there evidence of a linear relationship between total hours and job satisfaction? Provide a reason for your answer.

(e)the ANOVA table of the regression model fit is shown below (with some items missing)

 df SS MS Significance F Regression ?? ?? 142419 0.0012 Residual 20 8074.6720 403.7340 Total 21 13824.591

What proportion of the variation in the response variable can be explained by the variation in the explanatory variable in the simple linear regression model? Please show your working to support your answer

(f) construct a 95% confidence interval estimate of the population mean job satisfaction for employees who works 55 hours per week. The sample mean total hours worked per week was 51.1818 and the sample standard deviation was 13.7517. please show your working to support your answer.

(g)